EPPS 6356 Data Visualization Project
This storyboard delivers our final project product by visualizing Formula 1 Racing data focused on analyzing information on the drivers and different circuits.
Multiple linear regression was utilized to determine which factors
are important to evaluate the best driver.
Wins = b0 + (Pole Wins) X1 + (Total Points) X2 + (Fastest Laps) X3 +
(Podiums) X4 + (1st WDC Age) X5 + e
Note: b0 is the intercept of the regression line and e is the model
error (residuals) or the variation in the model
R^2 = 0.9904, p-value = 5.769e-06
All factors were significant except Fastest Laps and Age. Tried to
evaluate the height factor, however, the p-value was truly not
significant since the p-value was 0.72785.
The coefficient plot lists each of the coefficients and the effect they
have on the model. The further away the point is from the dotted line
set at zero, the larger of an impact there is.
These 2 graphs are created using the “f1dataR” library!